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Abstract

A model based reconstruction algorithm that exploits translational symmetries for photoacoustic microscopy to drastically reduce the memory cost is presented. The memory size needed to store the model matrix is independent of the number of acquisitions at different positions. This helps us to overcome one of the main limitations of previous algorithms. Furthermore, using the algebraic reconstruction technique and building the model matrix “on the fly”, we have obtained fast reconstructions of simulated and experimental data on both two- and three-dimensional grids using a traditional dark field photoacoustic microscope and a standard personal computer.

Figures (7)

: (Top) Representation of a row of the weight matrix W corresponding to a specific time point and a detector characterized by the position of its focal point rd1. (Bottom) Representation of a row of the weight matrix for the same time point, corresponding to the same detector but now situated at position rd2 (focal point). A large area of the bottom image can be seen as a translation of the top image. The weights correspond to a circular transducer with a radius of 12.7 mm and a numerical aperture of 0.36 that is, situated in the positive part of the z axis.

(Left) Raw, simulated PAM data of the imaged objects obtained after the linear scan. (Right) Model based reconstruction after three iterations of the ART algorithm using the low memory cost generator matrix. All five objects (shown in Fig. 1) are clearly resolved in both dimensions. All data are normalized to the maximum.

The 3D reconstruction of the thread after three iterations of the ART algorithm using the low memory cost generator matrix. The reconstructed image is represented with 30 equally spaced axial slices. The image is normalized to the maximum.